Audio coding

ABSTRACT

According to a first aspect of the invention, at least part of an audio signal is coded in order to obtain an encoded signal, the coding comprising predictive coding the at least part of the audio signal in order to obtain prediction coefficients which represent temporal properties, such as a temporal envelope, of the at least part of the audio signal, transforming the prediction coefficients into a set of times representing the prediction coefficients, and including the set of times in the encoded signal. Especially the use of a time domain derivative or equivalent of the Line Spectral Representation is advantageous in coding such prediction coefficients, because with this technique times or time instants are well defined which makes them more suitable for further encoding. For overlapping frame analysis/synthesis for the temporal envelope, redundancy in the Line Spectral Representation at the overlap can be exploited. Embodiments of the invention exploit this redundancy in an advantageous manner.

The invention relates to coding at least part of an audio signal.

In the art of audio coding, Linear Predictive Coding (LPC) is well knownfor representing spectral content. Further, many efficient quantizationschemes have been proposed for such linear predictive systems, e.g. LogArea Ratios [1], Reflection Coefficients [2] and Line SpectralRepresentations such as Line Spectral Pairs or Line Spectral Frequencies[3, 4, 5].

Without going into much detail on how the filter-coefficients aretransformed to a Line Spectral Representation (reference is made to [6,7, 8, 9, 10] for more detail), the results are that an M-th orderall-pole LPC filter H(z) is transformed to M frequencies, often referredto as Line Spectral Frequencies (LSF). These frequencies uniquelyrepresent the filter H(z). As an example see FIG. 1. Note that forclarity the Line Spectral Frequencies have been depicted in FIG. 1 aslines towards the amplitude response of the filter, although they arenothing more than just frequencies, and thus do not in themselvescontain any amplitude information whatsoever.

An object of the invention is to provide advantageous coding of at leastpart of an audio signal. To this end, the invention provides a method ofencoding, an encoder, an encoded audio signal, a storage medium, amethod of decoding, a decoder, a transmitter, a receiver and a system asdefined in the independent claims. Advantageous embodiments are definedin the dependent claims.

According to a first aspect of the invention, at least part of an audiosignal is coded in order to obtain an encoded signal, the codingcomprising predictive coding the at least part of the audio signal inorder to obtain prediction coefficients which represent temporalproperties, such as a temporal envelope, of the at least part of theaudio signal, transforming the prediction coefficients into a set oftimes representing the prediction coefficients, and including the set oftimes in the encoded signal. Note that times without any amplitudeinformation suffice to represent the prediction coefficients.

Although a temporal shape of a signal or a component thereof can also bedirectly encoded in the form of a set of amplitude or gain values, ithas been the inventor's insight that higher quality can be obtained byusing predictive coding to obtain prediction coefficients whichrepresent temporal properties such as a temporal envelope andtransforming these prediction coefficients to into a set of times.Higher quality can be obtained because locally (where needed) highertime resolution can be obtained compared to fixed time-axis technique.The predictive coding may be implemented by using the amplitude responseof an LPC filter to represent the temporal envelope.

It has been a further insight of the inventors that especially the useof a time domain derivative or equivalent of the Line SpectralRepresentation is advantageous in coding such prediction coefficientsrepresenting temporal envelopes, because with this technique times ortime instants are well defined which makes them more suitable forfurther encoding. Therefore, with this aspect of the invention, anefficient coding of temporal properties of at least part of an audiosignal is obtained, attributing to a better compression of the at leastpart of an audio signal.

Embodiments of the invention can be interpreted as using an LPC spectrumto describe a temporal envelope instead of a spectral envelope and thatwhat is time in the case of a spectral envelope, now is frequency andvice versa, as shown in the bottom part of FIG. 2. This means that usinga Line Spectral Representation now results in a set of times or timeinstances instead of frequencies. Note that in this approach times arenot fixed at predetermined intervals on the time-axis, but that thetimes themselves represent the prediction coefficients.

The inventors realized that when using overlapping frameanalysis/synthesis for the temporal envelope, redundancy in the LineSpectral Representation at the overlap can be exploited. Embodiments ofthe invention exploit this redundancy in an advantageous manner.

The invention and embodiments thereof are in particular advantageous forthe coding of a temporal envelope of a noise component in the audiosignal in a parametric audio coding schemes such as disclosed in WO01/69593-A1. In such a parametric audio coding scheme, an audio signalmay be dissected into transient signal components, sinusoidal signalcomponents and noise components. The parameters representing thesinusoidal components may be amplitude, frequency and phase. For thetransient components the extension of such parameters with an envelopedescription is an efficient representation.

Note that the invention and embodiments thereof can be applied to theentire relevant frequency band of the audio signal or a componentthereof, but also to a smaller frequency band.

These and other aspects of the invention will be apparent from theelucidated with reference to the accompanying drawings.

In the drawings:

FIG. 1 shows an example of an LPC spectrum with 8 poles withcorresponding 8 Line Spectral Frequencies according to prior art;

FIG. 2 shows (top) using LPC such that H(z) represents a frequencyspectrum, (bottom) using LPC such that H(z) represents a temporalenvelope;

FIG. 3 shows a stylized view of exemplary analysis/synthesis windowing;

FIG. 4 shows an example sequence of LSF times for two subsequent frames;

FIG. 5 shows matching of LSF times by shifting LSF times in a frame krelative to a previous frame k-1;

FIG. 6 shows weighting functions as function of overlap; and

FIG. 7 shows a system according to an embodiment of the invention.

The drawings only show those elements that are necessary to understandthe embodiments of the invention.

Although the below description is directed to the use of an LPC filterand the calculation of time domain derivatives or equivalents of LSFs,the invention is also applicable to other filters and representationswhich fall within the scope of the claims.

FIG. 2 shows how a predictive filter such as an LPC filter can be usedto describe a temporal envelope of an audio signal or a componentthereof. In order to be able to use a conventional LPC filter, the inputsignal is first transformed from time domain to frequency domain by e.g.a Fourier Transform. So in fact, the temporal shape is transformed in aspectral shape which is coded by a subsequent conventional LPC filterwhich is normally used to code a spectral shape. The LPC filter analysisprovides prediction coefficients which represent the temporal shape ofthe input signal. There is a trade-off between time-resolution andfrequency resolution. Say that e.g. the LPC spectrum would consist of anumber of very sharp peaks (sinusoids). Then the auditory system is lesssensitive to time-resolution changes, thus less resolution is needed,also the other way around, e.g. within a transient the resolution of thefrequency spectrum does not need to be accurate. In this sense one couldsee this as a combined coding, the resolution of the time-domain isdependent on the resolution of the frequency domain and vice versa. Onecould also employ multiple LPC curves for the time-domain estimation,e.g. a low and a high frequency band, also here the resolution could bedependent on the resolution of the frequency estimation etc, this couldthus be exploited.

An LPC filter H(z) can generally be described as:${H(z)} = {\frac{1}{A(z)} = \frac{1}{1 + {a_{1}z^{- 1}} + {a_{2}z^{- 2}} + \ldots + {a_{m}z^{- m}}}}$The coefficients α_(i), with i running from 1 to m, are the predictionfilter coefficients resulting from the LPC analysis. The coefficientsα_(i) determine H(z).

To calculate the time domain equivalents of the LSFs, the followingprocedure can be used. Most of this procedure is valid for a generalall-pole filter H(z), so also for frequency domain. Other proceduresknown for deriving LSFs in the frequency domain can also be used tocalculate the time domain equivalents of the LSFs.

The polynomial A(z) is split into two polynomials P(z) and Q(z) of orderm+1. The polynomial P(z) is formed by adding a reflection coefficient(in lattice filter form) of +1 to A(z), Q(z) is formed by adding areflection coefficient of −1. There's a recurrent relation between theLPC filter in the direct form (equation above) and the lattice form:A _(i)(z)=A _(i-1)(z)+K _(i) z ^(−i) A _(i-1)(z ⁻¹)with i=1, 2, . . . , m, A₀(z)=1 and k_(i) the reflection coefficient.

The polynomials P(z) and Q(z) are obtained by:P(z)=A _(m)(z)+z ^(−(m+1)) A _(m)(z ⁻¹)Q(z)=A _(m)(z)−z ^(−(m+1)) A _(m)(z ⁻¹)

The polynomials P(z)=1+p_(l)z⁻¹+p₂z⁻²+ . . . +p_(m)z^(−m)+z_(−(m+1)) andQ(z)=1+q₁z⁻¹+q₂z⁻²+ . . . +q_(m)z^(−m)−z^(−(m+1)) obtained in this wayare even symmetrical and anti-symmetrical:

-   p₁=p_(m) q₁=−q_(m)-   p₂=p_(m-1) q₂=−q_(m-1)-   . .-   . .

Some important properties of these polynomials:

-   -   All zeros of P(z) and Q(z) are on the unit circle in the        z-plane.    -   The zeros of P(z) and Q(z) are interlaced on the unit circle and        do not overlap.    -   Minimum phase property of A(z) is preserved after quantization        guaranteeing stability of H(z).

Both polynomials P(z) and Q(z) have m+1 zeros. It can be easily seenthat z=−1 and z=1 are always a zero in P(z) or Q(z). Therefore they canbe removed by dividing by 1+z⁻¹ and 1-z⁻¹. If m is even this leads to:${P^{\prime}(z)} = \frac{P(z)}{1 + z^{- 1}}$${Q^{\prime}(z)} = \frac{Q(z)}{1 - z^{- 1}}$

If m is odd: P^(′)(z) = P(z)${Q^{\prime}(z)} = \frac{Q(z)}{\left( {1 - z^{- 1}} \right)\left( {1 + z^{- 1}} \right)}$

The zeros of the polynomials P′ (z) and Q′ (z) are now described byz_(i)=e^(it) because the LPC filter is applied in the temporal domain.The zeros of the polynomials P′ (z) and Q′ (z) are thus fullycharacterized by their time t, which runs from 0 to π over a frame,wherein 0 corresponds to a start of the frame and π to an end of thatframe, which frame can actually have any practical length, e.g. 10 or 20ms. The times t resulting from this derivation can be interpreted astime domain equivalents of the line spectral frequencies, which timesare further called LSF times herein. To calculate the actual LSF times,the roots of P′ (z) and Q′ (z) have to be calculated. The differenttechniques that have been proposed in [9], [10], [11] can also be usedin the present context.

FIG. 3 shows a stylized view of an exemplary situation for analysis andsynthesis of temporal envelopes. At each frame k a, not necessarilyrectangular, window is used to analyze the segment by LPC. So for eachframe, after conversion, a set of N LSF times is obtained. Note that Nin principal does not need to be constant, although in many cases thisleads to a more efficient representation. In this embodiment we assumethat the LSF times are uniformly quantized, although other techniqueslike vector quantization could also be applied here.

Experiments have shown that in an overlap area as shown in FIG. 3 thereis often redundancy between the LSF times of frame k-1 with those offrame k. Reference is also made to FIGS. 4 and 5. In embodiments of theinvention which are described below, this redundancy is exploited tomore efficiently encode the LSF times, which helps to better compressthe at least part of an audio signal. Note that FIGS. 4 and 5 show usualcases wherein the LSF times of frame k in the overlapping area are notidentical but however rather close to the LSF times in frame k-1.

First Embodiment Using Overlapping Frames

In a first embodiment using overlapping frames it is assumed that thedifferences between LSF times of overlapping areas can be, perceptually,neglected or result in an acceptable loss in quality. For a pair of LSFtimes, one in the frame k-1 and one in the frame k, a derived LSF timeis derived which is a weighted average of the LSF times in the pair. Aweighted average in this application is to be construed as including thecase where only one out of the pair of LSF times is selected. Such aselection can be interpreted as a weighted average wherein the weight ofthe selected LSF time is one and the weight of the non-selected time iszero. It is also possible that both LSF times of the pair have the sameweight.

For example, assume LSF times {l₀, l₁, l₂, . . . , l_(N)} for frame k-1and {l₀, l₁, l₂, . . . , l_(M)} for frame k as shown in FIG. 4. The LSFtimes in frame k are shifted such that a certain quantization level l isin the same position in each of the two frames. Now assume that thereare three LSF times in the overlapping area for each frame, as is thecase for FIG. 4 and FIG. 5. Then the following corresponding pairs canbe formed: {l_(N-2,k-1) l_(0,k), l_(N-1,k-1) l_(1,k), l_(Nk-1) l_(2,k)}.In this embodiment, a new set of three derived LSF times is constructedbased on the two original sets of three LSF times. A practical approachis to just take the LSF times of frame k-1 (or k), and calculate the LSFtimes of frame k (or k-1) by simply shifting the LSF times of frame k-1(or k) to align the frames in time. This shifting is performed in boththe encoder and the decoder. In the encoder the LSFs of the right framek are shifted to match the ones in the left frame k-1. This is necessaryto look for pairs and eventually determine the weighted average.

In preferred embodiments, the derived time or weighted average isencoded into the bit-stream as a ‘representation level’ which is aninteger value e.g. from 0 until 255 (8 bits) representing 0 until pi. Inpractical embodiments also Huffman coding is applied. For a first framethe first LSF time is coded absolutely (no reference point), allsubsequent LSF times (including the weighted ones at the end) are codeddifferentially to their predecessor. Now, say frame k could make use ofthe ‘trick’ using the last 3 LSF times of frame k-1. For decoding, framek then takes the last three representation levels of frame k-1 (whichare at the end of the region 0 until 255) and shift them back to its owntime-axis (at the beginning of the region 0 until 255). All subsequentLSF times in frame k would be encoded differentially to theirpredecessor starting with the representation level (on the axis of framek) corresponding to the last LSF in the overlap area. In case frame kcould not make use of the ‘trick’ the first LSF time of frame k would becoded absolutely and all subsequent LSF times of frame k differential totheir predecessor.

A practical approach is to take averages of each pair of correspondingLSF times, e.g. (l_(N-2,k-1)+l_(0,k))/2, (l_(N-1,k-1)+l_(1,k))/2 and(l_(N,k-1)+l_(2,k))/2.

An even more advantageous approach takes into account that the windowstypically show a fade-in/fade-out behavior as shown in FIG. 3. In thisapproach a weighted mean of each pair is calculated which givesperceptually better results. The procedure for this is as follows. Theoverlapping area corresponds to the area (π-r, π). Weight functions arederived as depicted in FIG. 6. The weight to the times of the left framek-1 for each pair separately is calculated as:$w_{k - 1} = \frac{\pi - l_{mean}}{r}$where l_(mean) is the mean (average) of a pair, e.g.:l_(mean)=(l_(N-2,k-1)+l_(0,k))/2.The weight for frame k is calculated as w_(k)=1−w_(k-1).The new LSF times are now calculated as:l _(weighted) =l _(k-1) w _(k-1) +l _(k) w _(k)where l_(k-1) and l_(k) form a pair. Finally the weighted LSF times areuniformly quantized.

As the first frame in a bit-stream has no history, the first frame ofLSF times always need to be coded without exploitation of techniques asmentioned above. This may be done by coding the first LSF timeabsolutely using Huffman coding, and all subsequent valuesdifferentially to their predecessor within a frame using a fixed Huffmantable. All frames subsequent to the first frame can in essence makeadvantage of an above technique. Of course such a technique is notalways advantageous. Think for instance of a situation where there arean equal number of LSF times in the overlap area for both frames, butwith a very bad match. Calculating a (weighted) mean might then resultin perceptual deterioration. Also the situation where in frame k-1 thenumber of LSF times is not equal to the number of LSF times in frame kis preferably not defined by an above technique. Therefore for eachframe of LSF times an indication, such as a single bit, is included inthe encoded signal to indicate whether or not an above technique isused, i.e. should the first number of LSF times be retrieved from theprevious frame or are they in the bit-stream? For example, if theindicator bit is 1: the weighted LSF times are coded differentially totheir predecessor in frame k-1, for frame k the first number of LSFtimes in the overlap area are derived from the LSFs in frame k-1. If theindicator bit is 0, the first LSF time of frame k is coded absolutely,all following LSFs are coded differentially to their predecessor.

In a practical embodiment, the LSF time frames are rather long, e.g.1440 samples at 44.1 kHz; in this case only around 30 bits per secondare needed for this extra indication bit. Experiments showed that mostof the frames could make use of the above technique advantageously,resulting in net bit savings per frame.

Further Embodiment Using Overlapping Frames

According to a further embodiment of the invention, the LSF time data isloss-lessly encoded. So instead of merging the overlap-pairs to singleLSF times, the differences of the LSF times in a given frame are encodedwith respect to the LSF times in another frame. So in the example ofFIG. 3 when the values l₀ until l_(N) are retrieved of frame k-1, thefirst three values l₀ until l₃ from frame k are retrieved by decodingthe differences (in the bit-stream) to l_(N-2), l_(N-1), l_(N) of framek-1 respectively. By encoding an LSF time with reference to an LSF timein an other frame which is closer in time than any other LSF time in theother frame, a good exploitation of redundancy is obtained because timescan best be encoded with reference to closest times. As theirdifferences are usually rather small, they can be encoded quiteefficiently by using a separate Huffman table. So apart from the bitdenoting whether or not to use a technique as described in the firstembodiment, for this particular example also the differencesl_(0,k)−l_(N-2,k-1), l_(1,k)−l_(N-1,k-1), l_(2,k)−l_(N,k-1) are placedin the bit-stream, in the case the first embodiment is not used for theoverlap concerned.

Although less advantageously, it is alternatively possible to encodedifferences relative to other LSF times in the previous frame. Forexample, it is possible to only code the difference of the first LSFtime of the subsequent frame relative to the last LSF time of theprevious frame and then encode each subsequent LSF time in thesubsequent frame relative to the preceding LSF time in the same frame,e.g. as follows: for frame k-1: l_(N-1)−l_(N-2), l_(N)−l_(N-1) andsubsequently for frame k: l_(0,k)−l_(N,k-1), l_(1,k)−l_(0,k) etc.

System Description

FIG. 7 shows a system according to an embodiment of the invention. Thesystem comprises an apparatus 1 for transmitting or recording an encodedsignal [S]. The apparatus 1 comprises an input unit 10 for receiving atleast part of an audio signal S, preferably a noise component of theaudio signal. The input unit 10 may be an antenna, microphone, networkconnection, etc. The apparatus 1 further comprises an encoder 11 forencoding the signal S according to an above described embodiment of theinvention (see in particular FIGS. 4, 5 and 6) in order to obtain anencoded signal. It is possible that the input unit 10 receives a fullaudio signal and provides components thereof to other dedicatedencoders. The encoded signal is furnished to an output unit 12 whichtransforms the encoded audio signal in a bit-stream [S] having asuitable format for transmission or storage via a transmission medium orstorage medium 2. The system further comprises a receiver orreproduction apparatus 3 which receives the encoded signal [S] in aninput unit 30. The input unit 30 furnishes the encoded signal [S] to thedecoder 31. The decoder 31 decodes the encoded signal by performing adecoding process which is substantially an inverse operation of theencoding in the encoder 11 wherein a decoded signal S′ is obtained whichcorresponds to the original signal S except for those parts which werelost during the encoding process. The decoder 31 furnishes the decodedsignal S′ to an output unit 32 that provides the decoded signal S′. Theoutput unit 32 may be reproduction unit such as a speaker forreproducing the decoded signal S′. The output unit 32 may also be atransmitter for further transmitting the decoded signal S′ for exampleover an in-home network, etc. In the case the signal S′ isreconstruction of a component of the audio signal such as a noisecomponent, then the output unit 32 may include combining means forcombining the signal S′ with other reconstructed components in order toprovide a full audio signal.

Embodiments of the invention may be applied in, inter alia, Internetdistribution, Solid State Audio, 3G terminals, GPRS and commercialsuccessors thereof.

It should be noted that the above-mentioned embodiments illustraterather than limit the invention, and that those skilled in the art willbe able to design many alternative embodiments without departing fromthe scope of the appended claims. In the claims, any reference signsplaced between parentheses shall not be construed as limiting the claim.This word ‘comprising’ does not exclude the presence of other elementsor steps than those listed in a claim. The invention can be implementedby means of hardware comprising several distinct elements, and by meansof a suitably programmed computer. In a device claim enumerating severalmeans, several of these means can be embodied by one and the same itemof hardware. The mere fact that certain measures are recited in mutuallydifferent dependent claims does not indicate that a combination of thesemeasures cannot be used to advantage.

REFERENCES

-   [1] R. Viswanathan and J. Makhoul, “Quantization properties of    transmission parameters in linear predictive sytems”, IEEE Trans.    Acoust., Speech, Signal Processing, vol. ASSP-23, pp. 309-321, June    1975.-   [2] A. H. Gray, Jr. and J. D. Markel, “Quantization and bit    allocation in speech processing”, IEEE Trans. Acoust., Speech,    Signal Processing, vol. ASSP-24, pp. 459-473, December 1976.-   [3] F. K. Soong and B.-H. Juang, “Line Spectrum Pair (LSP) and    Speech Data Compression”, Proc. ICASSP-84, Vol. 1, pp. 1.10.1-4,    1984.-   [4] K. K. Paliwal, “Efficient Vector Quantization of LPC Parameters    at 24 Bits/Frame”, IEEE Trans. on Speech and Audio Processing, Vol.    1, pp. 3-14, January 1993.-   [5] F. K. Soong and B.-H. Juang, “Optimal Quantization of LSP    Parameters”, IEEE Trans. on Speech and Audio Processing, Vol. 1, pp.    15-24, January 1993.-   [6] F. Itakura, “Line Spectrum Representation of Linear Predictive    Coefficients of Speech Signals”, J. Acoust. Soc. Am., 57, 535 (A),    1975.-   [7] N. Sagumura and F. Itakura, “Speech Data Compression by LSP    Speech Analysis-Synthesis Technique”, Trans. IECE '81/8, Vol. J    64-A, No. 8, pp. 599.606.-   [8] P. Kabal and R. P. Ramachandran, “Computation of line spectral    frequencies using chebyshev polynomials”, IEEE Trans. on ASSP, vol.    34, no. 6, pp. 1419-1426, December 1986.-   [9] J. Rothweiler, “A root finding algorithm for line spectral    frequencies”, ICASSP-99.-   [10] Engin Erzin and A. Enis Cetin, “Interframe Differential Vector    Coding of Line Spectrum Frequencies”, Proc. of the Int. Conf. on    Acoustic, Speech and Signal Processing 1993 (ICASSP '93), Vol. II,    pp. 25-28, 27 Apr. 1993

1. A method of coding at least part of an audio signal in order toobtain an encoded signal, the method comprising the steps of: predictivecoding the at least part of the audio signal in order to obtainprediction coefficients which represent temporal properties, such as atemporal envelope, of the at least part of the audio signal;transforming the prediction coefficients into a set of timesrepresenting the prediction coefficients; and including the set of timesin the encoded signal.
 2. A method as claimed in claim 1, wherein thepredictive coding is performed by a using a filter and wherein theprediction coefficients are filter coefficients.
 3. A method as claimedin claim 1, wherein the predictive coding is a linear predictive coding.4. A method as claimed in claim 1, wherein prior to the predictivecoding step a time domain to frequency domain transform is performed onthe at least part of an audio signal in order to obtain a frequencydomain signal, and wherein the predictive coding step is performed onthe frequency domain signal rather than on the at least part of an audiosignal.
 5. A method as claimed in claim 1, wherein the times are timedomain derivatives or equivalents of line spectral frequencies.
 6. Amethod as claimed in claim 1, wherein the at least part of an audiosignal is segmented in at least a first frame and a second frame andwherein the first frame and the second frame have an overlap includingat least one time of each frame.
 7. A method as claimed in claim 6,wherein for a pair of times consisting of one time of the first frame inthe overlap and one time of the second frame in the overlap, a derivedtime is included in the encoded signal, which derived time is a weightedaverage of the one time of the first frame and the one time of thesecond frame.
 8. A method as claimed in claim 7, wherein the derivedtime is equal to a selected one of the times of the pair of times.
 9. Amethod as claimed in claim 7, wherein a time closer to a boundary of aframe has lower weight than a time further away from said boundary. 10.A method as claimed in claim 6, wherein a given time of the second frameis differentially encoded with respect to a time in the first frame. 11.A method as claimed in claim 10, wherein the given time of the secondframe is differentially encoded with respect to a time in the firstframe which is closer in time to the given time in the second frame thanany other time in the first frame.
 12. A method as claimed in claim 7,wherein further an indicator, such as a single bit, is included in theencoded signal, which indicator indicates whether or not the encodedsignal includes a derived time in the overlap to which the indicatorrelates.
 13. A method as claimed in claim 7, wherein further anindicator, such as a single bit, is included in the encoded signal,which indicator indicates the type of coding which is used to encode thetimes or derived times in the overlap to which the indicator relates.14. An encoder for coding at least part of an audio signal in order toobtain an encoded signal, the encoder comprising: means for predictivecoding the at least part of the audio signal in order to obtainprediction coefficients which represent temporal properties, such as atemporal envelope, of the at least part of the audio signal; means fortransforming the prediction coefficients into a set of timesrepresenting the prediction coefficients; and means for including theset of times in the encoded signal.
 15. An encoded signal representingat least part of an audio signal, the encoded signal including a set oftimes representing prediction coefficients which prediction coefficientsrepresent temporal properties, such as a temporal envelope, of the atleast part of the audio signal.
 16. An encoded signal as claimed inclaim 15, wherein the times are related to at least a first frame and asecond frame in the at least part of an audio signal and wherein thefirst frame and the second frame have an overlap including at least onetime of each frame, and wherein the encoded signal includes at least onederived time, which derived time is a weighted average of the one timeof the first frame and the one time of the second frame.
 17. An encodedsignal as claimed in claim 16, the encoded signal further comprising anindicator, such as a single bit, which indicator indicates whether ornot the encoded signal includes a derived time in the overlap to whichthe indicator relates.
 18. A storage medium having stored thereon anencoded signal as claimed in claim
 15. 19. A method of decoding anencoded signal representing at least part of an audio signal, theencoded signal including a set of times representing predictioncoefficients which prediction coefficients represent temporalproperties, such as a temporal envelope, of the at least part of theaudio signal, the method comprising the steps of: deriving the temporalproperties, such as the temporal envelope, from the set of times andusing these temporal properties in order to obtain a decoded signal, andproviding the decoded signal.
 20. A method of decoding as claimed inclaim 19, wherein the method comprises the step of transforming the setof times in order to obtain the prediction coefficients, and wherein thetemporal properties are derived from the prediction coefficients ratherthan from the set of times.
 21. A method of decoding as claimed in claim19, wherein the times are related to at least a first frame and a secondframe in the at least part of an audio signal and wherein the firstframe and the second frame have an overlap including at least one timeof each frame, and wherein the encoded signal includes at least onederived time, which derived time is a weighted average of a pair oftimes consisting of one time of the first frame in the overlap and onetime of the second frame in the overlap in the original at least part ofan audio signal, wherein the method comprises further the step of usingthe at least one derived time in decoding the first frame as well as indecoding the second frame.
 22. A method of decoding as claimed in claim21, wherein the encoded signal further comprising an indicator, such asa single bit, which indicator indicates whether or not the encodedsignal includes a derived time in the overlap to which the indicatorrelates, the method further comprising the steps of: obtaining theindicator from the encoded signal, only in the case that the indicatorindicates that the overlap to which the indicator relates does include aderived time, performing the step of using the at least one derived timein decoding the first frame as well as in decoding the second frame. 23.A decoder for decoding an encoded signal representing at least part ofan audio signal, the encoded signal including a set of timesrepresenting prediction coefficients which prediction coefficientsrepresent temporal properties, such as a temporal envelope, of the atleast part of the audio signal, the method comprising the steps of:deriving the temporal properties, such as the temporal envelope, fromthe set of time and using these temporal properties in order to obtain adecoded signal, and providing the decoded signal.
 24. A transmittercomprising: an input unit for receiving at least part of an audiosignal, an encoder as claimed in claim 14 for encoding the at least partof an audio signal to obtain an encoded signal, and an output unit fortransmitting the encoded signal.
 25. A receiver comprising: an inputunit for receiving an encoded signal representing at least part of anaudio signal, a decoder as claimed in claim 23 for decoding the encodedsignal to obtain a decoded signal, and an output unit for providing thedecoded signal.
 26. A system comprising a transmitter as claimed inclaim 24.